• Korea Trade Review
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• v.44 no.2
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• pp.189-202
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• 2019

The Harmonized System comprises about 5,000 commodity groups; each identified by a six digit code, arranged in a legal and logical structure and is supported by well-defined rules to achieve uniform classification. This study reviews the appropriateness of Korea Customs Service and Tax Tribunal's customs classification decisions concerning the interpretation and application of the Harmonized System for certain ITA goods. Korea Customs Service had classified arbitrary and had not applied in dubio pro reo principle. This paper finds that 57% of Korea Customs Service's classification decisions have erred. Korea government need to take measures to secure uniform interpretation of the HS and its periodic updating in light of developments in technology and changes in trade patterns. This paper suggest to amend customs law and regulation concerning classification committee.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.25-33
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• 2015

From the viewpoint of applications to manufacturing, data mining is a useful method to find the meaningful knowledge or information about states of processes. But the data from manufacturing processes usually have two characteristics which are multicollinearity and imbalance distribution of data. Two characteristics are main causes which make bias to classification rules and select wrong variables as important variables. In the paper, we propose a new data mining procedure to solve the problem. First, to determine candidate variables, we propose the multiple hypothesis test. Second, to make unbiased classification rules, we propose the decision tree learning method with different weights for each category of quality variable. The experimental result with a real PDP (Plasma display panel) manufacturing data shows that the proposed procedure can make better information than other data mining procedures.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.588-595
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• 2003

High resolution panchromatic satellite images collected by sensors such as IRS-1C/D and KOMPSAT-1 have a spatial resolution of approximately 6 ${\times}$ 6 ㎡, making them very attractive for urban applications. However, the spectral information present in these images is very limited. In order to overcome this limitation, an object-oriented classification approach is used to identify basic land cover types in urban areas. Before an image can be classified it is segmented at different aggregation levels using a multiresolution segmentation approach. In the course of this segmentation various statistical as well as topological information is collected for each segment. Based on this information it is possible to classify image objects and to arrive at much better results than by looking only at single pixels. Using an image recorded by KOMPSAT-1 over the City of Vienna a land cover classification was carried out for two areas. One was used to set up the rules for the different land cover types. The second subset was classified based on these rules, only adjusting some of the functions governing the classification process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.614-621
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• 2006

We have implemented a multiclassifier learning approach in a GA-based inductive learning environment that learns classification rules that are similar to rules used in PROSPECTOR. In the multiclassifier learning approach, a classification system is constructed with several classifiers that are obtained by running a GA-based learning system several times to improve the overall performance of a classification system. To implement the multiclassifier learning approach, we need a decision-making scheme that can draw a decision using multiple classifiers. In this paper, we introduce two decision-making schemes: one is based on combining posterior odds given by classifiers to each class and the other one is a voting scheme based on ranking assigned to each class by classifiers. We also present empirical results that evaluate the effect of the multiclassifier learning approach on the GA-based inductive teaming environment.

• International Journal of Naval Architecture and Ocean Engineering
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• v.4 no.4
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• pp.386-402
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• 2012

In this paper, a method to estimate ice loads as a function of the buttock angle of an icebreaker is presented with respect to polycrystalline freshwater ice. Ice model tests for different buttock angles and impact velocities are carried out to investigate ice pressure loads and tendencies of ice pressure loads in terms of failure modes. Experimental devices were fabricated with an idealized icebreaker bow shape, and medium-scale ice specimens were used. A dry-drop machine with a freefall system was used, and four pressure sensors were installed at the bottom to estimate ice pressure loads. An estimation equation was suggested on the basis of the test results. We analyzed the estimation equation for design ice loads of the International Association of Classification Societies (IACS) classification rules. We suggest an estimation equation considering the relation between ice load, buttock angle, and velocity by modifying the equations given in the IACS classification rules.

• Journal of the Korean housing association
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• v.24 no.3
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• pp.55-64
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• 2013

The purpose of the study was to make an improvement of residential management regulations so that the inhabitants of rental housing can manage their housing in efficient and transparent manners by comparing and analyzing in standard management rules of rental housing. The research method were as follows: 1) The analysis framework utilized result of preceding research composed 6 types of management works and 36 items of subcategories by researcher 2) The standard management rules of rental housing used analysis utilized to draw up after a revision of Rental Housing Act in 2000 and to operate in management of rental housing now. 3) The analysis method used content analysis. The management rules of rental housing utilized a total of 5 rules such as management rules of SH corporation (2011), LH corporation (2000), peoples' solidarity for participatory democracy (2000), Citizens' Alliance (2000) and Gyeonggi-do (2001). The research result were as follows: 1) Overall, the management rules of rental housing included faithfully works of operation management and administration management 2) The type of operation management regulated centrally items related resident committee. and The type of administration management regulated centrally items related accounting management. 3) The management rules of SH corporation and LH corporation regulated centrally operation management, maintenance management and etiquette for the basic living as compared with the other rules.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9B
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• pp.577-588
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• 2007

The rapid growth of the Internet has stimulated the development of various new applications and services, and the service providers and the Internet users now require different levels of service qualities rather than current best-effort service which treats all incoming packet equally. Therefore, next generation routers should provide the various levels of services. In order to provide the quality of services, incoming packets should be classified into flows according to pre-defined rules, and this should be performed for all incoming packets in wire-speed. Packet classification not only involves multi-dimensional search but also finds the highest priority rule among all matching rules. Area-based quad-trie is a very good algorithm that constructs a two-dimensional trie using source and destination prefix fields. However, it performs the linear search for the prefix length, and hence it does not show very good search performance. In this paper, we propose to apply binary search on length to the area-based quad-trie algorithm. In improving the search performance, we also propose two new algorithms considering the priority of rules in building the trie.

• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.730-741
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• 2011

With the development of the internet and computer technology, the amount of information through the internet is increasing rapidly and it is managed in document form. For this reason, the research into the method to manage for a large amount of document in an effective way is necessary. The conventional document categorization method used only the keywords of related documents for document classification. However, this paper proposed keyword extraction method of based on association rule. This method extracts a set of related keywords which are involved in document's category and classifies representative keyword by using the classification rule proposed in this paper. In addition, this paper proposed the preprocessing method for efficient keywords creation and predicted the new document's category. We can design the classifier and measure the performance throughout the experiment to increase the profile's classification performance. When predicting the category, substituting all the classification rules one by one is the major reason to decrease the process performance in a profile. Finally, this paper suggested automatically categorizing plan which can be applied to hierarchical category architecture, extended from simple category architecture.

• Journal of KIISE
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• v.43 no.1
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• pp.80-86
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• 2016

A speech-act is a behavior intended by users in an utterance. Speech-act classification is important in a dialogue system. The machine learning and rule-based methods have mainly been used for speech-act classification. In this paper, we propose a speech-act classification method based on the combination of support vector machine (SVM) and transformation-based learning (TBL). The user's utterance is first classified by SVM that is preferentially applied to categories with a low utterance rate in training data. Next, when an utterance has negative scores throughout the whole of the categories, the utterance is applied to the correction phase by rules. The results from our method were higher performance over the baseline system long with error-reduction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.521-527
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• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.